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musharna

plant-genomics-mcp

batch_get_gene_xrefs

Retrieve cross-references for up to 50 plant gene loci in parallel from Ensembl Plants, returning count, xref list, and by-database rollup per locus.

Instructions

Batch variant of get_gene_xrefs. Fans out per-locus xref lookups over Ensembl Plants in parallel (up to 50 loci). Each results[locus] is the full single-locus shape (count + xrefs[] + by_db rollup).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lociYesList of locus identifiers (1–50). Successes land in results[locus]; PlantGenomicsError failures in errors[locus].
organismNoPlant organism — accepts canonical slug (arabidopsis_thaliana), scientific or common name, or NCBI taxidarabidopsis_thaliana

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesThe batch tool name, e.g. batch_resolve_locus_to_uniprot
countYesNumber of loci in the input list
resultsYeslocus → per-locus result dict (same shape as the single-locus tool)
errorsYeslocus → '[ClassName] message' for PlantGenomicsError failures
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, description discloses parallelism, limit of 50 loci, result structure, and error handling. Could mention performance or side effects but sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with key info, no wasted words. Efficient and clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given complexity (batch, parallel, error handling) and presence of output schema, description covers main aspects. Could detail output schema further but not needed when schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% so baseline 3. Description adds context: loci identifiers, organism flexibility, and clarifies error vs success mapping. Adds value beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it is a batch variant of get_gene_xrefs, performs parallel lookups for up to 50 loci, and describes the output shape. Distinguishes from the single-locus sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Indicates usage for multiple loci via 'batch variant' and 'fans out...in parallel'. Implicitly when not to use (single locus) via sibling naming, but lacks explicit alternatives or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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